Automatic Data Processing Stock Current Valuation

ADP Stock  USD 246.31  3.00  1.23%   
Valuation analysis of Automatic Data Processing helps investors to measure Automatic Data's intrinsic value by examining its available valuation indicators, including the cash flow records, the balance sheet account changes and income statement patterns. As of 04/23/2024, Enterprise Value is likely to grow to about 61 B, while Enterprise Value Over EBITDA is likely to drop 9.76. Fundamental drivers impacting Automatic Data's valuation include:
Price Book
23.1966
Enterprise Value
101.7 B
Enterprise Value Ebitda
18.5
Price Sales
5.3896
Forward PE
24.2718
Fairly Valued
Today
246.31
Please note that Automatic Data's price fluctuation is very steady at this time. Calculation of the real value of Automatic Data Processing is based on 3 months time horizon. Increasing Automatic Data's time horizon generally increases the accuracy of value calculation and significantly improves the predictive power of the methodology used.
Our valuation method for Automatic Data Processing is useful when determining the fair value of the Automatic stock, which is usually determined by what a typical buyer is willing to pay for full or partial control of Automatic Data. Since Automatic Data is currently traded on the exchange, buyers and sellers on that exchange determine the market value of Automatic Stock. However, Automatic Data's intrinsic value may or may not be the same as its current market price, in which case there is an opportunity to profit from the mispricing, assuming the market price will eventually merge with its intrinsic value.
Historical Market  246.31 Real  252.66 Target  259.93 Hype  246.12
The real value of Automatic Stock, also known as its intrinsic value, is the underlying worth of Automatic Data Processing Company, which is reflected in its stock price. It is based on Automatic Data's financial performance, assets, liabilities, growth prospects, management team, or industry conditions. The intrinsic value of Automatic Data's stock can be calculated using various methods such as discounted cash flow analysis, price-to-earnings ratio, or price-to-book ratio. That value may differ from its current market price, which is determined by supply and demand factors such as investor sentiment, market trends, news, and other external factors that may influence Automatic Data's stock price. It is important to note that the real value of any stock may change over time based on changes in the company's performance.
221.68
Downside
252.66
Real Value
253.52
Upside
Estimating the potential upside or downside of Automatic Data Processing helps investors to forecast how Automatic stock's addition to their portfolios will impact the overall performance. We also use other valuation drivers to help us estimate the true value of Automatic Data more accurately as focusing exclusively on Automatic Data's fundamentals will not take into account other important factors:
Earnings
Estimates (0)
LowProjectedHigh
2.682.782.92
Details
Hype
Prediction
LowEstimatedHigh
245.26246.12246.98
Details
21 Analysts
Consensus
LowTarget PriceHigh
236.54259.93288.52
Details

Automatic Data Processing Company Current Valuation Analysis

Automatic Data's Enterprise Value is a firm valuation proxy that approximates the current market value of a company. It is typically used to determine the takeover or merger price of a firm. Unlike Market Cap, this measure takes into account the entire liquid asset, outstanding debt, and exotic equity instruments that the company has on its balance sheet. When a takeover occurs, the parent company will have to assume the target company's liabilities but will take possession of all cash and cash equivalents.

Enterprise Value

 = 

Market Cap + Debt

-

Cash

More About Current Valuation | All Equity Analysis

Current Automatic Data Current Valuation

    
  101.72 B  
Most of Automatic Data's fundamental indicators, such as Current Valuation, are part of a valuation analysis module that helps investors searching for stocks that are currently trading at higher or lower prices than their real value. If the real value is higher than the market price, Automatic Data Processing is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.

Automatic Current Valuation Driver Correlations

Understanding the fundamental principles of building solid financial models for Automatic Data is extremely important. It helps to project a fair market value of Automatic Stock properly, considering its historical fundamentals such as Current Valuation. Since Automatic Data's main accounts across its financial reports are all linked and dependent on each other, it is essential to analyze all possible correlations between related accounts. However, instead of reviewing all of Automatic Data's historical financial statements, investors can examine the correlated drivers to determine its overall health. This can be effectively done using a conventional correlation matrix of Automatic Data's interrelated accounts and indicators.
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Click cells to compare fundamentals

Automatic Current Valuation Historical Pattern

Today, most investors in Automatic Data Stock are looking for potential investment opportunities by analyzing not only static indicators but also various Automatic Data's growth ratios. Consistent increases or drops in fundamental ratios usually indicate a possible pattern that can be successfully translated into profits. However, when comparing two companies, knowing each company's current valuation growth rates may not be enough to decide which company is a better investment. That's why investors frequently use a static breakdown of Automatic Data current valuation as a starting point in their analysis.
   Automatic Data Current Valuation   
       Timeline  
Enterprise Value can be a useful tool to compare companies with different capital structures. Long term liability and current cash or cash equivalents can have a huge impact on market valuation of a given company.
Competition

In accordance with the recently published financial statements, Automatic Data Processing has a Current Valuation of 101.72 B. This is much higher than that of the Professional Services sector and significantly higher than that of the Industrials industry. The current valuation for all United States stocks is significantly lower than that of the firm.

Automatic Current Valuation Peer Comparison

Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Automatic Data's direct or indirect competition against its Current Valuation to detect undervalued stocks with similar characteristics or determine the stocks which would be a good addition to a portfolio. Peer analysis of Automatic Data could also be used in its relative valuation, which is a method of valuing Automatic Data by comparing valuation metrics of similar companies.
Automatic Data is currently under evaluation in current valuation category among related companies.

Automatic Data ESG Sustainability

Some studies have found that companies with high sustainability scores are getting higher valuations than competitors with lower social-engagement activities. While most ESG disclosures are voluntary and do not directly affect the long term financial condition, Automatic Data's sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Automatic Data's managers, analysts, and investors.
Environment Score
Governance Score
Social Score

Automatic Fundamentals

About Automatic Data Fundamental Analysis

The Macroaxis Fundamental Analysis modules help investors analyze Automatic Data Processing's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Automatic Data using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Automatic Data Processing based on its fundamental data. In general, a quantitative approach, as applied to this company, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.
Please read more on our fundamental analysis page.

Pair Trading with Automatic Data

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Automatic Data position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Automatic Data will appreciate offsetting losses from the drop in the long position's value.

Moving against Automatic Stock

  0.71EXPO Exponent Earnings Call This WeekPairCorr
  0.54FC Franklin Covey Financial Report 26th of June 2024 PairCorr
  0.52FORR Forrester Research Financial Report 2nd of May 2024 PairCorr
  0.51VIRC Virco Manufacturing Report 26th of April 2024 PairCorr
  0.42ARC ARC Document Solutions Financial Report 1st of May 2024 PairCorr
The ability to find closely correlated positions to Automatic Data could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Automatic Data when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Automatic Data - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Automatic Data Processing to buy it.
The correlation of Automatic Data is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Automatic Data moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Automatic Data Processing moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Automatic Data can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching
When determining whether Automatic Data Processing is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if Automatic Stock is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Automatic Data Processing Stock. Highlighted below are key reports to facilitate an investment decision about Automatic Data Processing Stock:
Check out Automatic Data Piotroski F Score and Automatic Data Altman Z Score analysis.
Note that the Automatic Data Processing information on this page should be used as a complementary analysis to other Automatic Data's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.

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When running Automatic Data's price analysis, check to measure Automatic Data's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Automatic Data is operating at the current time. Most of Automatic Data's value examination focuses on studying past and present price action to predict the probability of Automatic Data's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Automatic Data's price. Additionally, you may evaluate how the addition of Automatic Data to your portfolios can decrease your overall portfolio volatility.
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Is Automatic Data's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Automatic Data. If investors know Automatic will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Automatic Data listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth
0.092
Dividend Share
5.15
Earnings Share
8.59
Revenue Per Share
45.09
Quarterly Revenue Growth
0.063
The market value of Automatic Data Processing is measured differently than its book value, which is the value of Automatic that is recorded on the company's balance sheet. Investors also form their own opinion of Automatic Data's value that differs from its market value or its book value, called intrinsic value, which is Automatic Data's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Automatic Data's market value can be influenced by many factors that don't directly affect Automatic Data's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Automatic Data's value and its price as these two are different measures arrived at by different means. Investors typically determine if Automatic Data is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Automatic Data's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.